Tiffany Michelle Barnes

Tiffany Michelle Barnes
North Carolina State University | NCSU · Department of Computer Science

PhD, NC State, 2003

About

336
Publications
46,069
Reads
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3,815
Citations
Citations since 2016
183 Research Items
2681 Citations
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20162017201820192020202120220100200300400500
20162017201820192020202120220100200300400500
Introduction
My research focuses on how to improve education and games through data, analytics, and artificial intelligence.
Additional affiliations
April 2010 - August 2012
University of North Carolina at Charlotte
Position
  • Professor (Associate)
August 2004 - April 2010
University of North Carolina at Charlotte
Position
  • Research Assistant
Education
August 2000 - December 2003
North Carolina State University
Field of study
  • Computer Science
August 1996 - May 2000
North Carolina State University
Field of study
  • Computer Science & Mathematics
August 1992 - December 1995
North Carolina State University
Field of study
  • Computer Science & Mathematics

Publications

Publications (336)
Article
While Reinforcement learning (RL), especially Deep RL (DRL), has shown outstanding performance in video games, little evidence has shown that DRL can be successfully applied to human-centric tasks where the ultimate RL goal is to make the human-agent interactions productive and fruitful. In real-life, complex, human-centric tasks, such as education...
Conference Paper
Full-text available
Positive student self-efficacy has been linked to undergraduate computer science students' improved retention rates and success in the major, with self-efficacy in programming being particularly important. To improve poor self-efficacy in programming , especially for novices, we must understand the moments that affect students' self-perceived progr...
Article
Many block-based programming environments have proven to be effective at engaging novices in learning programming. However, most offer only restricted access to the outside world, limiting learners to commands and computing resources built in to the environment. Some allow learners to drag and drop files, connect to sensors and robots locally or is...
Article
Full-text available
Research on intelligent tutoring systems has been exploring data-driven methods to deliver effective adaptive assistance. While much work has been done to provide adaptive assistance when students seek help, they may not seek help optimally. This had led to the growing interest in proactive adaptive assistance, where the tutor provides unsolicited...
Conference Paper
Metacognitive skills have been commonly associated with preparation for future learning in deductive domains. Many researchers have regarded strategy- and time-awareness as two metacognitive skills that address how and when to use a problem-solving strategy, respectively. It was shown that students who are both strategy-and time-aware (StrTime) out...
Preprint
Learning to derive subgoals reduces the gap between experts and students and makes students prepared for future problem solving. Researchers have explored subgoal labeled instructional materials with explanations in traditional problem solving and within tutoring systems to help novices learn to subgoal. However, only a little research is found on...
Preprint
Data-driven programming feedback systems can help novices to program in the absence of a human tutor. Prior evaluations showed that these systems improve learning in terms of test scores, or task completion efficiency. However, crucial aspects which can impact learning or reveal insights important for future improvement of such systems are ignored...
Preprint
Full-text available
Metacognitive skills have been commonly associated with preparation for future learning in deductive domains. Many researchers have regarded strategy- and time-awareness as two metacognitive skills that address how and when to use a problem-solving strategy, respectively. It was shown that students who are both strategy-and time-aware (StrTime) out...
Preprint
Research on intelligent tutoring systems has been exploring data-driven methods to deliver effective adaptive assistance. While much work has been done to provide adaptive assistance when students seek help, they may not seek help optimally. This had led to the growing interest in proactive adaptive assistance, where the tutor provides unsolicited...
Article
Historically, female students have shown low interest in the field of computer science. Previous computer science curricula have failed to address the lack of female-centered computer science activities, such as socially relevant and real-life applications. Our new summer camp curriculum introduces the topics of artificial intelligence (AI), machin...
Article
Student modeling sits at the epicenter of adaptive learning technology. In contrast to the voluminous work on student modeling for well-defined domains such as algebra, there has been little research on student modeling in programming (SMP) due to data scarcity caused by the unbounded solution spaces of open-ended programming exercises. In this wor...
Conference Paper
Full-text available
Deductive domains are typical of many cognitive skills in that no single problem-solving strategy is always optimal for solving all problems. It was shown that students who know how and when to use each strategy (StrTime) outperformed those who know neither and stick to the default strategy (Default). In this work, students were trained on a logic...
Preprint
Full-text available
Knowledge tracing (KT) models are a popular approach for predicting students' future performance at practice problems using their prior attempts. Though many innovations have been made in KT, most models including the state-of-the-art Deep KT (DKT) mainly leverage each student's response either as correct or incorrect, ignoring its content. In this...
Article
Theories on learning show that formative feedback that is immediate, specific, corrective, and positive is essential to improve novice students’ motivation and learning. However, most prior work on programming feedback focuses on highlighting student's mistakes, or detecting failed test cases after they submit a solution. In this article, we presen...
Article
The COVID-19 pandemic led to an urgent need for professional development (PD) experiences to support teacher learning across hybrid and digital contexts. This study investigates teachers' experiences in a Virtual Pivot, a PD workshop designed to support computational thinking integration into disciplinary teaching. Participants were 151 middle and...
Conference Paper
Classroom dashboards are designed to help instructors effectively orchestrate classrooms by providing summary statistics, activity tracking, and other information. Existing dashboards are generally specific to an LMS or platform and they generally summarize individual work, not group behaviors. However, CS courses typically involve constellations o...
Preprint
Full-text available
Classroom dashboards are designed to help instructors effectively orchestrate classrooms by providing summary statistics, activity tracking, and other information. Existing dashboards are generally specific to an LMS or platform and they generally summarize individual work, not group behaviors. However, CS courses typically involve constellations o...
Article
In interactive e-learning environments such as Intelligent Tutoring Systems, pedagogical decisions can be made at different levels of granularity. In this work, we focus on making decisions at two levels: whole problems vs. single steps and explore three types of granularity: problem-level only (Prob-Only), step-level only (Step-Only) and both prob...
Preprint
Full-text available
Discussing a problem is the first step in help-seeking, and online forums are one of the fastest ways students can communicate their concerns, doubts, and requests for help in a blended classroom environment. There are many studies aimed at detecting the relationship between a student's individual forum use and their individual performance on assig...
Article
Although there has been much work on procedural content generation for other game genres, very few researchers have tackled automated content generation for educational games. In this paper, we present a template-based, automatic puzzle generator for an educational puzzle programming game called BOTS. Two experts created their own new puzzles and e...
Chapter
Intelligent Tutoring Systems (ITS) provide a powerful tool for students to learn in an adaptive, personalized, and goal-oriented manner. In recent years, Reinforcement Learning (RL) has shown to be capable of leveraging previous student data to induce effective pedagogical policies for future students. One of the most desirable goals of these polic...
Chapter
Reinforcement Learning (RL) is learning what action to take next by mapping situations to actions so as to maximize cumulative rewards. In recent years RL has achieved great success in inducing effective pedagogical policies for various interactive e-learning environments. However, it is often prohibitive to identify the critical pedagogical decisi...
Article
Research has shown assistance can provide many benefits to novices lacking the mental models needed for problem solving in a new domain. However, varying approaches to assistance, such as subgoals and next-step hints, have been implemented with mixed results. Next-Step hints are common in data-driven tutors due to their straightforward generation f...
Conference Paper
Full-text available
Based on strategy-awareness (knowing which problem-solving strategy to use) and time-awareness (knowing when to use it), students are categorized into Rote (neither type of awareness), Dabbler (strategy-aware only) or Selective (both types of awareness). It was shown that Selective is often significantly more prepared for future learning than Rote...
Preprint
Full-text available
Open-ended programming increases students' motivation by allowing them to solve authentic problems and connect programming to their own interests. However, such open-ended projects are also challenging, as they often encourage students to explore new programming features and attempt tasks that they have not learned before. Code examples are effecti...
Preprint
Research has shown assistance can provide many benefits to novices lacking the mental models needed for problem solving in a new domain. However, varying approaches to assistance, such as subgoals and next-step hints, have been implemented with mixed results. Next-Step hints are common in data-driven tutors due to their straightforward generation f...
Conference Paper
Full-text available
Since the Advanced Placement Computer Science Principles (AP CSP) course has been released, it has vastly increased the need for highly trained CSP teachers who are prepared to bring CS to a diverse group of students. We have designed professional development (PD) workshops for high school teachers learning to teach this new CSP course, basing our...
Conference Paper
Full-text available
The Covid-19 pandemic has offered new challenges and opportunities for teaching and research. It has forced constraints on in-person gathering of researchers, teachers, and students, and conversely, has also opened doors to creative instructional design. This paper describes a novel approach to designing an online, synchronous teacher professional...
Article
Within intelligent tutoring systems, considerable research has investigated hints, including how to generate data-driven hints, what hint content to present, and when to provide hints for optimal learning outcomes. However, less attention has been paid to how hints are presented. In this paper, we propose a new hint delivery mechanism called “Asser...
Conference Paper
Full-text available
Learning theories and psychological research show that positive feedback during practice can increase learners' motivation , and correlates with their learning. In our prior work, we built a system that provides immediate positive feedback using expert-authored features, and found a promising impact on students' performance and engagement with the...
Preprint
Determining when and whether to provide personalized support is a well-known challenge called the assistance dilemma. A core problem in solving the assistance dilemma is the need to discover when students are unproductive so that the tutor can intervene. Such a task is particularly challenging for open-ended domains, even those that are well-struct...
Preprint
Within intelligent tutoring systems, considerable research has investigated hints, including how to generate data-driven hints, what hint content to present, and when to provide hints for optimal learning outcomes. However, less attention has been paid to how hints are presented. In this paper, we propose a new hint delivery mechanism called "Asser...
Chapter
Infusing Computing is a three-year professional development project that supports middle and high school teachers in integrating computational thinking into their disciplinary teaching. During the first two years of the project, 266 teachers (99 individuals, 167 members of school-based teacher teams) attended week-long summer workshops and particip...
Article
This special issue presents five invited research articles featuring distinguished contributions to the Fourth IEEE Special Technical Community on Broadening Participation (STCBP) Conference for Research on Equity and Sustained Participation in Engineering, Computing, and Technology (RESPECT 2019). The articles advance our understanding of challeng...
Preprint
Teamwork, often mediated by version control systems such as Git and Apache Subversion (SVN), is central to professional programming. As a consequence, many colleges are incorporating both collaboration and online development environments into their curricula even in introductory courses. In this research, we collected GitHub logs from two programmi...
Conference Paper
Full-text available
Curriculum-integrated games can provide teachers with data to help them decide when and how to intervene with individual students. Based on our prior work observing teachers using ST Math, teachers may not be able to attend to a dashboard or student screens to determine who might need intervention. We therefore set out to determine how much data we...